Conventionally, to achieve advanced services, it has been attempted to impart detailed attribution information to individual data. On the other hand, an attempt has been considered to utilize relationships among data to services (see Non-Patent Document 1). Especially, social relationships such as a relationship between a person and a person and a relationship between the context of movements of persons and locations have been drawn attention, and the relationship of such data is shown as a relationship graph.
The relationship graph shows, as shown in FIG. 3A, objects, such as, e.g., persons, goods, places, and contents, as nodes, and shows the presence or absence of the mutual relationship of those objects. Further, the strength of the relationship between nodes directly connected with each other is given by a link length, and the strength of the relationship between nodes connected via another node is given by a path length.
By using the information observed in the real world or online as an input source, the object group contained in the input source is created as nodes. Further, a link between nodes is also created, and therefore a small relationship graph (subgraph) is created.
Further, by connecting a plurality of subgraphs via a common node, a large one relationship graph is created, and stored in a database (see Patent Document 1). In connecting them, when there exists the same link redundantly, the link length becomes shorter.
Further, the relationship graph stored in a database is referred to by various applications and utilized. In cases where a relation graph of persons only is formed using information of SNS (Social Networking Service) as an input source, although there is no direct link with a certain person, it is possible to present (recommend) another person which is small in path length as a future friend. For example, in an e-commerce (electronic commerce) by a mobile terminal, in cases where a relationship graph is formed based on a visit history to places and a purchase history of goods, when a certain consumer visited a certain place, it is possible to recommend goods which is small in path length from the consumer and the place on the relationship graph.